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upload fastwam base checkpoints and LIBERO fine-tuned checkpoints
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# FastWAM Base
This directory contains the complete FastWAM initialization used by the
FluxVLA FastWAM LIBERO full-finetuning recipe.
## Contents
- `fastwam_base_full.safetensors`: bf16 FastWAM state dict initialized with
seed 42. It contains the video DiT, VAE, text encoder, and ActionDiT
parameters.
- `tokenizer/`: UMT5 tokenizer files used for online text encoding.
- `manifest.json`: package metadata and integrity information.
The package intentionally excludes task-specific text-embedding caches. Text
prompts are encoded online by the model loaded from the complete checkpoint.
After downloading this directory to `./checkpoints/fastwam_base`, configure
FastWAM with:
```python
pretrained_name_or_path = (
'./checkpoints/fastwam_base/fastwam_base_full.safetensors')
tokenizer_path = './checkpoints/fastwam_base/tokenizer'
```
The corresponding FluxVLA recipe is
`configs/fastwam/fastwam_libero_full_finetune.py`.